Preventing maritime accidents: The role of human factors and cognitive performance
BackgroundThe maritime industry, despite rigorous safety measures, remains a high-risk sector due to persistent human errors.ObjectiveThis study aims to assess mental workload, accuracy, and attention across various mental states and explore the relationships among key variables affecting cognitive performance through a Bayesian network (BN) analysis.MethodsData were collected from 51 officers at a maritime training center using demographic surveys and the NASA Task Load Index (NASA-TLX) mental workload index. Participants were then subjected to three different simulation scenarios, during which their physiological responses and brain waves were recorded.ResultsResults indicated that effort scored the highest and failure the lowest among the dimensions assessed. Notably, the average heart rate increased from 74.33 beats per minute at rest to 85.92 after the second scenario, signifying heightened physiological stress. Post-scenario analyses showed an increase in attention and alertness levels compared to the resting state, while meditation levels decreased. Physiological responses, including heart rate and blood pressure, were found to elevate after rest periods, correlating with decreased attention and increased mental workload, as evidenced by the BN findings.ConclusionsThese results underscore the intricate interplay between physiological responses and cognitive performance, highlighting the critical need for targeted strategies to mitigate human errors in maritime operations.
Authors
- Mehran Ghalenoei (ORCID: https://orcid.org/0000-0002-4012-9971)
- Omran Ahmadi (ORCID: https://orcid.org/0000-0003-3151-9991)
- Elmira Mohammadi (ORCID: https://orcid.org/0000-0002-8045-6969)
- Fatemeh Salimi (ORCID: https://orcid.org/0000-0003-1752-7194)
Institutions
- Tarbiat Modares University (IR)
- Qazvin University of Medical Sciences (IR)
Publication Details
- Journal
- Work
- Published
- 2025-08-25
- DOI
- https://doi.org/10.1177/10519815251367224
- Primary Topic
- Human-Automation Interaction and Safety
- Type
- article
- Field-Weighted Citation Impact
- 0.00